The High PerformanceComputing Center Stuttgart (HLRS)

The High Performance Computing Center was established in 1996 as the first national German High Performance Computing (HPC) center. It is a research and service institution affiliated to the University of Stuttgart offering services to academic users and industry.

HLRS is focusing on

The operation of leading edge HPC Systems

Teaching and training for HPC programming and simulation

Research in the field of HPC together with national and international partners

Collaboration with industry in R&D

Providing access to HPC systems through hww - a public private partnership with T-Systems and Porsche

Over the last 20 years HLRS has built up world-leading expertise in supporting and training end-users, from a variety of application fields with a focus on engineering. HLRS has built expertise in fields like parallel programming, numerical methods for HPC, visualization, Grid and Cloud concepts, and Big Data.

-> click to take a virtual tour of HLRS

Facts

Central Unit of Stuttgart University - High Performance Computing (HPC) since 1959

1st German National HPC Center founded 1996

Founding member of the German Gauss Centre for Supercomputing together with Juelich Supercomputing Center and Leibniz Rechenzentrum in 2007

Open to European users since 2010 through PRACE

HPC Service for German researchers and industry

Partner for HPC companies

Broad experience in collaborative research projects on national, European and international level

Sustainability at HLRS

Our Understanding of Sustainability

Acting sustainably is important for securing our future and that of future generations. Therefore, we are committed to sustainability. Our Sustainability Guidelines give us the action frame to protect environment and to consider social as well as economic interests. We want to set and achieve clearly defined sustainability targets. We intend to establish an open dialogue with our stakeholders and therefore we will regularly publish a sustainability report.

Simulation

When using simulations (mechanical or computer based), it becomes possible to make statements about the potential behavior of a subject, without a direct interaction with the physical entities. Prediction of the potential behavior of subjects under changed conditions is thus one of the most important roles of simulations. As just one obvious example, performing initial crash-tests with a computer-implemented model of a car instead of a real one will certainly save money even in the short run and, due to the ability to test many different scenarios, might even make the car (far) safer than it would be using time-consuming physical tests alone.

Parametric optimization techniques make it possible to automatically determine parameters of the chosen model that maximize or minimize specific properties. Here simulations fill the role of a solver, helping to determine one or more figures of merit connected to a given parameter set and model. Thus simulations pave the way to new designs that, in all likelihood, would not have been found using human expertise alone, due to the usually high dimensionality of the input space of the model.

As simulations may also require significant amounts of compute time, many simulation types are closely related to HPC (although most computing devices, from a smart phone to the most sophisticated super computer, are capable of running at least some type of simulations). And, as modern computing devices also become increasingly more powerful, models and thus simulations may become more detailed over time, giving them a better ability for valid predictions and thus raising their significance for society. It is important to note that simulations also affect many aspects of daily life, e.g. when estimating the spread of epidemics or simulations of pollutions in atmosphere.

In general, simulations, often in conjunction with powerful HPC devices, may provide us with tremendous opportunities that we should use. Some simulations even represent the only tool we have to make at least a rough forecast of what is to come. Not using them would be akin to driving blind-folded on a highway.